1. Linear regression model for metal–organic frameworks with CO2 adsorption based on topological data analysis
- Author
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Kazuto Akagi, Hisashi Naito, Takafumi Saikawa, Motoko Kotani, and Hirofumi Yoshikawa
- Subjects
Medicine ,Science - Abstract
Abstract Metal–organic frameworks (MOFs), self-assembled porous materials synthesized from metal ions and organic ligands, are promising candidates for the direct capture of CO2 from the atmosphere. In this work, we developed a regression model to predict the optimal component of the MOF that governs the amount of CO2 adsorption per volume based on experimentally observed adsorption and structure data combined with MOF adsorption sites. The structural descriptors were generated by topological data analysis with persistence diagrams, an advanced mathematical method for quantifying the rings and cavities within the MOF. This enables us to analyze direct effects and significance of the geometric structure of the MOF on the efficiency of CO2 adsorption in a novel way. The proposed approach is proved to be highly correlated with experimental data and thus offers an effective screening tool for MOFs with optimized structures.
- Published
- 2024
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